# Zaer Salem Abu-HammourUniversity of Jordan | UJ · Department of Mechatronics Engineering

Zaer Salem Abu-Hammour

Ph.D.

## About

56

Publications

20,627

Reads

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1,811

Citations

Introduction

Research Interests.....
Motion planning of robot manipulators, Inverse kinematics of robot manipulators, Control systems design (conventional and optimal), Model order reduction techniques, Numerical differentiation and integration, Numerical solution of ordinary and partial differential equations, Numerical solution of initial and boundary value problems, Continuous and discrete optimization problems, Continuous and conventional genetic algorithms.

Additional affiliations

September 2011 - present

September 2008 - September 2011

September 2006 - September 2008

Education

September 1998 - December 2002

**Pakistan Institute of Engineering and Applied Sciences, Pakistan Atomic Energy Commission.**

Field of study

- Systems Engineering

September 1996 - September 1998

**Pakistan Institute of Engineering and Applied Sciences, Pakistan Atomic Energy Commission.**

Field of study

- Systems Engineering

September 1986 - June 1991

## Publications

Publications (56)

Abstract: Land-use allocation (LUA) is a spatial optimization problem for urban planning in the future. The solution to this problem could
be enhancing the effectiveness of optimization algorithms that create a balance between urban needs and efficient LUAs. This study will
improve the performance of conventional genetic algorithms (cGAs) to addres...

In this paper, a novel continuous genetic algorithm (CGA) approach is proposed for the solution of Laplace, Poisson, Helmholtz, and nonlinear partial differential equations (PDEs) due to their importance as they are encountered in a variety of mathematical and physical systems. The approach is formulated by firstly converting the equation into an a...

Finding an accurate model to present the hysteresis nonlinearities behavior of the smart actuator has attracted the attention of the researchers in recent years, since an accurate model has an essential role in the position control application of these actuators. Different models have been developed to describe the hysteresis nonlinearities, the ge...

This paper proposes a two-loop position/speed control system for linear DC motors. The control system is based on the parameterization of lead compensator using the genetic algorithm (GA) optimization method. A performance criterion including the information of overshoot, rise time, settling time, and steady-state error is proposed as the objective...

In the recent years, using the fractional calculus has been increased in the applications of control engineering.This paper presents an Integer and Fractional PID controllers designed using particle swarm optimization technique for two different industrial applications, the first one is the heat solid. The simulation results show that the Integer P...

In this article, a residual power series technique for the power series solution of systems of initial value problems is introduced. The new approach provides the solution in the form of a rapidly convergent series with easily computable components using symbolic computation software. The proposed technique obtains Taylor expansion of the solution...

As the mathematical procedure of system modelling often leads to a comprehensive description, which causes significant difficulty in both analysis and control synthesis, it is necessary to find lower order models, which maintain the dominant characteristics of the original system. In this paper, different soft computing (named as artificial intelli...

A new model order reduction (MOR) technique for linear multi time scale discrete systems with substructure preservation is presented in this paper. The reduction process is performed based on two steps; system transformation and singular perturbation approximation (SPA). The system transformation step is performed to maintain the desired system sub...

A robust computational technique for model order reduction (MOR) of multi-time-scale discrete systems (single input single output (SISO) and multi-input multioutput (MIMO)) is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on th...

In this paper, an optimization algorithm is presented for solving systems of singular boundary value problems. In this technique, the system is formulated as an optimization problem by the direct minimization of the overall individual residual error subject to the given constraints boundary conditions, and is then solved using continuous genetic al...

In this paper, the solution of inverse kinematics problem of robot manipulators using genetic algorithms (GA) is presented. Two versions of genetic algorithms are used which include the conventional GA and the continuous GA. The inverse kinematics problem is formulated as an optimization problem based on the concept of minimizing the accumulative p...

The one-dimensional continuous genetic algorithm (CGA) previously developed by the principal author is extended and enhanced to deal with two-dimensional spaces in this paper. The enhanced CGA converts the partial differential equations into algebraic equations by replacing the derivatives appearing in the differential equation with their proper fi...

A new substructure preservation Sylvester-based model order reduction technique with application to power systems is presented in this article. The new approach is intended for multiple-input–multiple-output linear time invariant systems, given in the form of state-space realization with the objective of obtaining a proper reduced-order model (comp...

In this paper, a model-order reduction (MOR) technique with the advantage of critical frequency preservation capability is proposed using the particle swarm optimization (PSO). The new approach is capable of simplifying single-input single-output (SISO) systems as well as multi-input multi-output (MIMO) systems. If critical frequency preservation i...

In this paper, continuous genetic algorithm is introduced as an efficient solver for systems of second-order boundary value problems where smooth solution curves are used throughout the evolution of the algorithm to obtain the required nodal values of the unknown variables. The solution methodology is based on representing each derivative in the sy...

A new kind of optimization technique, namely, continuous genetic algorithm, is presented in this paper for numerically approximating the solutions of Troesch's and Bratu's problems. The underlying idea of the method is to convert the two differential problems into discrete versions by replacing each of the second derivatives by an appropriate diffe...

In this paper, a numerical algorithm, based on the use of genetic algorithm technique, is presented for solving a class of nonlinear systems of second-order boundary value problems. In this technique, the system is formulated as an optimization problem by the direct minimization of the overall individual residual error subject to the given constrai...

In this paper, Continuous Genetic Algorithms (CGAs) are used as an intelligent computational technique to provide a problem optimal solution. The problem is formulated as an optimization problem by the direct minimization of the performance index subject to constraints, and is then solved using a CGA. The presented approach has some advantages over...

In this work, a model order reduction (MOR) technique for a linear multivariable system is proposed using invasive weed optimization (IWO). This technique is applied with the combined advantages of retaining the dominant poles and the error minimization. The state space matrices of the reduced order system are chosen such that the dominant eigenval...

In this article, a new analytical method has been devised to solve higher-order initial value problems for ordinary differential equations. This method was implemented to construct a series solution for higher-order initial value problems in the form of a rapidly convergent series with easily computable components using symbolic computation softwar...

Modelling of linear dynamical systems is very important issue in science and engineering. The modelling process might be achieved by either the application of the governing laws describing the process or by using the input-output data sequence of the process. Most of the modelling algorithms reported in the literature focus on either determining th...

This work is concerned with the application of a continuous genetic algorithm (CGA) to solve the nonlinear optimization problem that results from the clearance process of nonlinear flight control laws. The CGA is used to generate a pilot command signal that governs the aircraft performance around certain points in the flight envelope about which th...

In this paper, the continuous genetic algorithm is applied for the solution of singular two-point boundary value problems, where smooth solution curves are used throughout the evolution of the algorithm to obtain the required nodal values. The proposed technique might be considered as a variation of the finite difference method in the sense that ea...

Solution of the chemical reactor problem, as an optimal control problem, using continuous genetic algorithms (CGAs) is presented in this paper. The proposed approach overcomes the drawbacks of the traditional approaches in terms of lack of efficiency, lack of accuracy and lack of robustness. The solution is based on the value of the performance ind...

Even though model order reduction (MOR) techniques for linear dynamical systems are developed rather properly, there are still quite a lot of issues to be considered. This paper addresses a novel MOR technique for multi-input multi-output system with dominant eigenvalue preservation, which leads to controller cost minimization. The new technique is...

In this paper we present with proof an explicit (n+1)-points method to approximate the m-th partial derivative to functions of two variables included mixed derivatives, then we generalize this method to functions of k variables, hence we can derive (r,m)-points finite difference formulas to functions of two variables and N-points finite difference...

A novel substructure (dominant eigenvalue) preserving genetic algorithm approach for model order reduction (MOR) of multi-time-scale systems is presented in this paper. The new technique is formulated based on genetic algorithms (GAs), sub-optimization and estimation. The GA predicts the elements of an upper triangular matrix form of the system sta...

This paper presents a new technique for model order reduction (MOR) that is based on an artificial neural network (ANN) prediction. The ANN-based MOR can be applied for different scale systems with substructure preservation. In the proposed technique, the ANN is implemented for predicting the unknown elements of the reduced order model. Prediction...

In this paper, the Continuous Genetic Algorithm (CGA), previously developed by the principal author, is applied for the solution of optimal control problems. The optimal control problem is formulated as an optimization problem by the direct minimization of the performance index subject to constraints, and is then solved using CGA. In general, CGA u...

In this paper, as a machine learning or system modeling, a novel genetic algorithm (GA) approach for solving university course timetabling problem is presented. The designed timetabling is free of any hard constraint violations and satisfies most of the soft constraints as much as realistically possible. When compared with other methods, the follow...

A frequency-based model order reduction (MOR) via genetic algorithm (GA) approach is presented in this paper. An exogenous autoregressive model with a smaller dimensionality, which can mimic the full order model, maybe obtained using the GA MOR approach. For a general MOR, the GA predicts the elements of the system state matrix [A] defined in a sta...

A novel genetic algorithm (GA) approach with frequency selectivity advantage for model order reduction (MOR) of multi-input–multi-output (MIMO) systems is presented in this article. Motivated by singular perturbation and other reduction techniques, the new MOR method is formulated using GAs, which can be applied to single-input–single-output (SISO)...

A novel continuous genetic algorithm (CGA) along with distance algorithm for solving collisions‐free path planning problem for robot manipulators is presented in this paper. Given the desired Cartesian path to be followed by the manipulator, the robot configuration as described by the D‐H parameters, and the available stationary obstacles in the wo...

A new method for simultaneously determining the order and the parameters of autoregressive moving average (ARMA) models is presented in this article. Given an ARMA (p, q) model in the absence of any information for the order, the correct order of the model (p, q) as well as the correct parameters will be simultaneously determined using genetic algo...

A novel method based on continuous genetic algorithms (CGAs) for the solution of Laplaces equations in two-dimensional rectangular regions has been developed. The algorithm converts the given differential equation into an algebraic equation in the first phase. After that, the overall residual error is calculated for all unknown nodes based on the v...

A new method for determining simultaneously the order and parameters of Auto Regressive Moving Average (ARMA) models is presented in this paper. ARMA models, which can be present in different fields such as communication systems, control systems, internet software and hardware models are determined using genetic algorithms (GAs). Given ARMA (p, q)...

To construct and optimize a neural network that is capable of predicting the occurrence of recurrent aphthous ulceration (RAU) based on a set of appropriate input data.
Artificial neural networks (ANN) software employing genetic algorithms to optimize the architecture neural networks was used. Input and output data of 86 participants (predisposing...

This paper addresses a novel model order reduction (MOR) technique with dominant substructure preservation. This process leads to cost minimization of the considered physical system which could be of any type from motors to circuitry packaging to software design. The new technique is formulated based on an artificial neural network (ANN) transforma...

In this paper we present a 13-point …nite di¤erence method for …nding positive (negative) solutions for the elliptic problems of the type r 2 u = g(x; y; u) in ; with boundary condition u = 0 in @, where is a real parameter and g : ! R is a smooth function. We will …nd some positive (or negative) numerical solution which can use to show that in whi...

A new method for model order reduction with eigenvalue preservation is presented in this paper. The new technique is formulated based on the system state matrix transformation which preserves the system eigenvalues and is accomplished using an artificial neural network training. A linear matrix inequality (LMI) numerical algorithm technique is used...

Second-order, two-point boundary-value problems are encountered in many engineering applications including the study of beam deflections, heat flow, and various dynamic systems. Two classical numerical techniques are widely used in the engineering community for the solution of such problems; the shooting method and finite difference method. These m...

In this paper, the authors describe a novel technique based on continuous genetic algorithms (CGAs) to solve the path generation problem for robot manipulators. We consider the following scenario: given the desired Cartesian path of the end-effector of the manipulator in a free-of-obstacles workspace, off-line smooth geometric paths in the joint sp...

In past, Gutowski proposed a special type of real-coded genetic algorithms, which is suited for continuous optimization problems with continuous and/or smooth solution curves. The algorithm uses smooth operators throughout the evolution process and results in smooth solution curves. However, Gutowski's algorithm is restricted to problems involving...

In this work, a model order reduction (MOR) technique for a linear multivariable system is proposed using the combined advantage of retaining the dominant poles and the error minimization using the particle swarm optimization. The state space matrices of the reduced order system are chosen such that the dominant eigenvalues of the full order system...